Increasingly the Internet is being used by individuals and enterprises as “the source” (authority) of information. For example, individuals regularly rely on content posted to wiki sites on the Internet without consideration to the fact that content posted there is not controlled and much of it can be specious. As another example, an employer often “Googles” a prospective employee (search for a person in the Google® search engine over the Internet) for purposes of doing research on that individual before an interview takes place with that individual. In this latter example, it seems little regard is given to that fact that content about an individual may have been maliciously placed there by others and may be entirely one sided and inaccurate. In fact, an interviewer may not even raise any issue found during a Google®, which is even worse for an interviewee because the interviewee is unaware of a predisposed biased held by the interviewer during the interview.
The problem is compounded with the rise of collaboration and virtual communities over the Internet. Here, the true identity of an author may be a real issue. That is, a single individual can assume a variety of personas during collaboration on content and appear to others to be entirely different individuals. The individual has an interest in preserving his/her anonymity whereas others have an interest in not being duped and in recognizing that multiple different content submissions as coming from a single virtual community member.
Content continues to grow at a phenomenal pace on the Internet as do the number of users; although the number of users is no indication as to the true growth in unique individuals that are appearing on the Internet (because one individual can assume multiple personas). So, the problem associated with validating content and associating it with particular individuals is becoming a daunting issue.
Moreover, even if content and attributors to that content were capable of being successfully identified and correlated, there is no mechanism to efficiently and coherently depict the trend or changes of such correlations over a corpus of content. Thus, digesting any such information can become an impractical exercise.
Therefore, improved techniques are needed for more efficiently determining contributions to and value assignments of content.